Systems and methods for determining and managing battery charging rules

ABSTRACT

The present disclosure relates to methods and associated systems for charging exchangeable energy storage devices positioned in a device-exchange station. The method includes, for example, (1) receiving demand information; (2) determining a charging plan for the device-exchange station at least partially based on a state-of-charge (SoC) of each of the exchangeable energy storage devices positioned in the device-exchange station, the demand information, and an available power of the device-exchange station; (3) generating a charging command for each of the exchangeable energy storage devices based on the charging rule for each of the exchangeable energy storage devices; and (4) transmitting the charging commands to the device-exchange station.

The present application claims the benefit of and priority to U.S.Provisional Application No. 62/612,160, filed Dec. 29, 2017, which isincorporated herein by reference in its entirety.

TECHNICAL FIELD

The present technology is directed to systems and methods fordetermining and managing charging rules of an exchangeable energystorage device positioned in a storage-device exchange station.

BACKGROUND

Many factors may affect a rechargeable battery's performance and lifespan, such as, the operating or charging conditions thereof. For anexchangeable battery system that handles a large number of exchangeablebatteries (which may include various types of batteries), it isdifficult to know how to properly charge each of the batteries so as tomaintain its best possible performance. It is even more difficult whenthese exchangeable batteries are deployed and have been used by varioususers under different operating conditions. Improper charging cannegatively impact a battery's energy-efficiency and life span.Therefore, it is advantageous to have an improved system and method toaddress this issue.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the disclosed technology will be described and explainedthrough the use of the accompanying drawings.

FIG. 1 is a schematic diagram illustrating a system in accordance withembodiments of the disclosed technology. The system is configured tocollect information from multiple sampling batteries.

FIG. 2 is a schematic diagram illustrating a system in accordance withembodiments of the disclosed technology. The system is configured todetermine a battery charging rule for an exchangeable battery to becharged.

FIG. 3 is a schematic diagram illustrating a station system inaccordance with embodiments of the disclosed technology.

FIG. 4 is a schematic diagram illustrating a server system in accordancewith embodiments of the disclosed technology.

FIGS. 5A-5C are schematic diagrams illustrating battery chargingcharacteristics or patterns in accordance with embodiments of thedisclosed technology.

FIG. 6 is a flowchart illustrating a method (e.g., performed by aprogrammed processor) in accordance with embodiments of the disclosedtechnology.

FIG. 7 is a flowchart illustrating a method (e.g., performed by aprogrammed processor) in accordance with embodiments of the disclosedtechnology.

The drawings are not necessarily drawn to scale. For example, thedimensions of some of the elements in the figures may be expanded orreduced to help improve the understanding of various embodiments.Similarly, some components and/or operations may be separated intodifferent blocks or combined into a single block for the purposes ofdiscussion of some of the embodiments. Moreover, although specificembodiments have been shown by way of example in the drawings anddescribed in detail below, one skilled in the art will recognize thatmodifications, equivalents, and alternatives will fall within the scopeof the appended claims.

DETAILED DESCRIPTION

In this description, references to “some embodiments,” “one embodiment,”or the like, mean that the particular feature, function, structure orcharacteristic being described is included in at least one embodiment ofthe disclosed technology. Occurrences of such phrases in thisspecification do not necessarily all refer to the same embodiment. Onthe other hand, the embodiments referred to are not necessarily mutuallyexclusive.

The present technology is directed to systems and methods for charging(or managing) exchangeable energy storage devices positioned in adevice-exchange station. In some embodiments, the device-exchangestation can be a battery-exchange station. In some embodiments, thedevice-exchange station can be a public station (e.g., to serve generalusers who subscribe a battery exchange plan, a semi-private station(e.g., to serve a particular group of users, such as users in acorporation, a school, a delivery fleet, etc.), or a private station(e.g., to serve a private group of users such as a household). Thepresent technology can provide, based on a predicted exchange demand, a“charging plan” for the battery-exchange station to charge the batteriestherein. In the present disclosure, the “charging plan” refers to a setof instructions (e.g., generated by a server) sent to thebattery-exchange station, and the instructions that are informativeregarding how to charge one or more batteries therein so as to meet apredicted exchange demand. An “overall charging plan” refers toinstructions for a server to manage multiple stations and charge thebatteries therein. The predicted exchange demand can be predictions onexchanges of batteries/battery usages during the following time periods,such as, 2 batteries to be picked up by a user in 2 hours, 4 batteriesto be picked up by another two users in 4 hours, etc. In someembodiments, the system includes a plurality of device-exchange stationsconnected to a server. The predicted exchange demands arecalculated/derived for each of the device-exchange stations by theserver based on the empirical information regarding exchange informationand predicted exchange information in the past. The server may store andmaintain (e.g., update periodically based on new coming data) thepredicted exchange demands of the device-exchange stations as the demandinformation in a memory of the server (or a database connected to theserver). By this arrangement, the present technology can effectivelyprepare exchangeable energy storage devices to meet the predicted demand(e.g., without wasting energy to charge, discharge, or maintain abattery that is not to be picked up in a near future, according to thepredicted demand). The exchangeable energy storage devices can be usedfor powering vehicles, mobile devices, etc. The exchangeable energystorage devices can also be used to power to households or the placesthat do not have mains electricity coverage.

In addition to forming charging plans based on the predicted demand, oneembodiment of the present technology also determines the charging planbased on one or more characteristics of the batteries (e.g., the“battery information” discussed below). In other words, these batteriescan be prepared/charged based on particular “charging rules” or“charging profiles” that correspond to characteristics thereof. Forexample, the charging rules can define how to charge a particularbattery with certain amount of current at a specific voltage for aperiod of time. The charging rules can vary based on one or more of thecharacteristics of the batteries together with the demand prediction(e.g., with the knowledge of how a battery ages or degrades as well as apredicted demand, the system knows how to charge the battery byselecting suitable charging rules/profiles). By this arrangement, thepresent technology can increase the lives of the batteries by selectingsuitable charging rules to charge/discharge the same (e.g., not tocharge a battery in a (relatively) fast charging process unlessnecessary so as to mitigate or reduce battery degradation). In someembodiments, the charging rules can be stored in a server. The servercan manage, maintain, and update these charging rules periodically or inresponse to a triggering event. In some embodiments, the triggeringevent includes an exchange of the exchangeable energy storage devicespositioned in the device-exchange station, a change to the availablepower, a change to demand information, and/or a reservation for theexchangeable energy storage devices positioned in the device-exchangestation.

In the present disclosure, once the suitable “charging rules” (or“charging profiles”) are determined, the system (e.g., a server) cangenerate a corresponding set of “charging commands” and then transmitthese charging commands to the battery-exchange station forimplementation. To elaborate, for example, the charging command is acommand specifying how to charge a particular battery at a certaincharging rate. The charging commands can be updated periodically (e.g.,by the server) based on the charging rules selected for each of theexchangeable energy storage devices and be sent to the multipledevice-exchange stations. For example, the state (e.g., SoC/temperature)of a battery can change with time, and accordingly the charging commandswill be updated.

In some embodiments, the present method can include, for example, (1)receiving demand information (e.g., a plurality of predicted exchangedemands) for a device-exchange station; (2) determining a charging planfor the device-exchange station at least partially based on astate-of-charge (SoC) of each of the exchangeable energy storage devicespositioned in the device-exchange station, the demand information, andan available power of the device-exchange station; (3) generating acharging command for each of the exchangeable energy storage devicesbased on the charging rule; and (4) transmitting the charging command tothe device-exchange station. The “charging plan” includes “chargingrules” selected or customized for each of energy storage devicespositioned in the device-exchange stations based on the characteristicsof the batteries and demand information, and the “charging commands” aregenerated based on the corresponding “charging rules.” For example, aserver can manage multiple device-exchange stations connected thereto bysending charging commands or the like to each of the stations.Description below discusses embodiments regarding how to generate/selectthe “charging rules.”

The present technology is also directed to systems and methods fordetermining and managing charging rules of an exchangeable battery basedon analyzing multiple sampling batteries with similar or the samecharacteristics of the exchangeable battery. The present disclosurerelates to a method and system for determining and managing chargingrules for exchangeable energy storage devices (e.g., batteries)positioned in an energy-storage-device exchange station. Moreparticularly, the present system provides a customized battery chargingrule (e.g., it describes how and when an exchangeable battery positionedin a battery-exchange station should be charged and can include chargingpatterns). Based on the customized battery charging rules (e.g.,determined based on one or more characteristics, features, and/orpatterns of the exchangeable battery), the battery can be charged toachieve one or more objectives such as increasing/maximizing batterylife spans, enhancing battery performances, and/or improving energyefficiency.

To achieve the foregoing objectives, the present system can firstcollect information from multiple sampling batteries. In someembodiments, the sampling batteries can include exchangeable batteriesthat are currently deployed in a battery-exchange marketplace. Forexample, the sampling batteries can include batteries that have beenused by a user (e.g., a battery plan subscriber) to power the user'selectric vehicle. In some embodiments, the sampling batteries caninclude batteries not yet on the market (e.g., those that are tested orstored in factories, warehouses, laboratories, etc.). In someembodiments, the disclosed system can collect information from multiplesources (e.g., battery exchange stations, electric vehicles, batteries,user mobile devices, etc.). In some embodiments, the disclosure systemcan collect information from a database.

The present system is configured to collect various types of batteryinformation, such as, one or more of (1) battery manufacturinginformation, (2) battery characteristic information, (3) batterycharging information, (4) battery usage information, and (5) othersuitable battery information (e.g., a unique battery identity serialnumber created by a battery exchange plan provider for tracking oradministrative purposes). Through analyzing these sets of informationand comparing the analysis results (e.g., as reference information) withthe characteristics of a battery (i.e., the above-described types ofbattery information that this battery may be) to be charged, the presentsystem can better understand the battery to be charged, and therefore isable to generate a detailed, customized charging rule for that battery.

Examples of the battery manufacturing information include batterymanufacturers (e.g., batteries made by different manufacturers may havedifferent characteristics, although their battery specifications may bethe same), manufacturing dates (e.g., batteries made on different datesmay have different characteristics), manufacturing batches (e.g.,batteries made in different batches may still have differentcharacteristics), hardware versions, firmware versions, cell types,and/or manufacturing serial numbers (e.g., batteries made in a batch canstill have different characteristics).

Examples of the battery characteristic information include a batterycapacity (e.g., full charge capacity, FCC), a battery dischargingcapacity (e.g., how much current can a battery provide under certainconditions), state-of-health (SOH), and/or a suggested battery workingtemperature (e.g., a temperature range such as 5 to 35 degrees Celsius).

Examples of the battery charging information include current state ofcharge (SOC) information, current battery temperature information,current cell temperature information, current circuit temperatureinformation, error status information (e.g., an error or a warningmessage produced by a battery management system (BMS) in the batteryresponsive to an abnormal charge or discharge event), a suggestedbattery charging temperature (e.g., a temperature range such as 25 to 40degrees Celsius), a suggested battery charging current (e.g., a constantor regulated current), a suggested battery charging voltage (e.g., aconstant or regulated voltage), a suggested battery charging cycle(e.g., at least one full charging per week), a suggested batterycharging speed (e.g., increasing from zero to 10% of the full capacityof a battery in 5 minutes), and/or a suggested battery charging time(e.g., not to be continuously charged for more than 5 hours).

Examples of battery usage information include battery age information(e.g., use time and/or cycle count), a battery direct current internalresistance (DCIR) information, an actual battery charging temperature(e.g., a battery was charged yesterday at 30 degrees Celsius and at 35degrees Celsius earlier today for 25 minutes), an actual batterycharging current (e.g., 1-200 Amperes), an actual battery chargingvoltage (e.g., 1-220 volts), an actual battery charging cycle (e.g., abattery has been through 50 full charge cycles and 125 partial cycles),an actual battery charging speed or charging rate (e.g., 20 Amperes perhour), an actual battery charging time (e.g., a battery was charged for56 minutes yesterday), an actual battery working temperature (e.g., abattery was operating at 35 degrees Celsius yesterday for 2 hours), andan actual battery discharging time (e.g., a battery discharges at itsfull current capacity for 66 minutes yesterday).

Examples discussed above are only embodiments of the present disclosure.In other embodiments or implementations, the present system can collectother types of information to support its analysis for customizedbattery charging rules. For example, the system of the presenttechnology can collect environmental information (e.g., weatherforecast) or other suitable information (e.g., a power outage noticefrom a power source used for charging, a fee schedule of a power source,an event notice indicating there will be an event held near a batteryexchange station in two days, etc.) that can potentially affect acharging process for the battery to be charged. In some embodiments, thefee schedule of a power source can indicate different fees by drawingpower during various time periods, so the charging rules for thebatteries in one battery exchange station can be selected/customizedbased on the above-described economic condition.

In some embodiments, system of the present technology analyzes thecollected information and generates or identifies a set of chargingpatterns for various types of batteries (e.g., as the characteristiccurves/lines shown in FIGS. 5A-5C). The generated or identified patternscan then be used as “reference information” or guidance for charging oneor more batteries to be charged to achieve an objective or goal. Forexample, based on the analysis, the present technology can generate acustomized charging rule that can maintain the maximum capacity of aparticular type of battery as long as possible. As another example, thepresent technology can generate a customized charging rule that canincrease/maximize the life span of a type of battery. In someembodiments, the present technology can generate a customized chargingrule that enables a specific type of battery to have a maximum number ofcharging cycles (e.g., after 500 charging cycles, the battery can stillhave 90% of its original capacity). In other embodiments, the presenttechnology can have other types of suitable objectives (e.g., customersatisfaction, battery performance, user experience, etc.).

In some embodiments, the customized battery charging rule can beselected from two or more candidate charging rules (e.g., the system caninclude 10 commonly-used charging patterns as the candidate chargingrules). For example, the disclosed system can generate a set ofcandidate charging rules for a system operator to select from. Forexample, the disclosed system can have a set of candidate charging rulesbased on “battery health” (e.g., charging cycles or possibledegradation). Battery “degradation” can mean a decrease of its fullcharge capacity (FCC) after charging/discharging. For example, the setof candidate charging rules based on “battery health” can include: (1)for batteries with 90-100% FCC (e.g., minor or no degradation) or within500 charging cycles, the system will stop charging these batteries whentheir battery cell temperatures exceed a threshold value (e.g., 50° C.);(2) for batteries with 80-90% FCC (e.g., acceptable degradation) orwithin 500-700 charging cycles, the system can keep charging thesebatteries when their battery cell temperatures range from, for example,50° C. to 55° C., if the system determines that a battery demand is high(e.g., to sacrifice the “battery health” to fulfill the battery demand);and (3) for batteries with less than 80% FCC or beyond 700 chargingcycles, the system will charge these batteries with a relative lowcurrent and start planning to remove such batteries from the system.

In some embodiments, the set of candidate charging rules can be designedto achieve one or more “battery health” goals. For example, thedisclosed system can provide three default candidate charging rules(i.e., Rules A, B, and C) for a system operator to choose from. Rule Acan be designed to achieve the highest possible battery healthy. Forexample, if Rule A is implemented to charge a battery, the battery isexpected to have a minor degradation (e.g., a 5%-10% decrease of itsFCC) after 700 charging cycles. Rule B can be designed to achieve anintermediate battery-healthy goal. For example, if Rule B is implementedto charge a battery, the battery is expected to have a minor degradation(e.g., a 5%-10% decrease of its FCC) after 500 charging cycles (e.g.,fewer than Rule A). Rule C can be designed to achieve a strategic goal(e.g., to fulfill battery demands) and maintain the battery health at anacceptable level. For example, if Rule C is implemented to charge abattery, the battery is expected to have a greater degradation (e.g., a10%-15% decrease of its FCC) after 500 charging cycles.

In the embodiments discussed above, Rule A can charge the battery with arelative low current for a relatively long time, compared to Rules B andC. For example, Rule A only allows a maximum 10-Ampere charging current,whereas Rule B allows a maximum 15-Ampere charging current. For example,Rule A needs one hour to complete a charging cycle from 20% FCC to 95%FCC, whereas Rule C only needs a half hour to do so.

The temperature thresholds for Rules A, B, and C can be different. Forexample, the temperature threshold for Rule A is 45°, the temperaturethreshold for Rule B is 52° C., and the temperature threshold for Rule Cis 55° C. The reference factors, thresholds and logic of charging rules(e.g., Rules A, B and C) can be set or updated based on (1) systempreference information; (2) results of statistical analyses; (3) resultsof machine training of historical data; (4) simulations ofhistorical/real-time data; and/or (5) results of experiments.

In some embodiments, the candidate charging rules can be determinedbased on environmental conditions such as an ambient temperature orhumidity. For example, the disclosed system can have a set of candidatecharging rules that applies to batteries located in a “hot” environment(e.g., over 38° C.), and have another set of candidate charging rulesthat applies to batteries located in a “cold” environment (e.g., below10° C.).

In some embodiments, the candidate charging rules can be determinedbased on predicted battery demands (e.g., within a predetermined timeinterval such as a hour). For example, the disclosed system can have aset of candidate charging rules that applies to batteries located in ahigh-demand battery exchange station (e.g., to charge batteries as soonas possible with a relatively high temperature tolerance, such as 55°C.), and have another set of candidate charging rules that applies tobatteries located in a low-demand battery exchange station (e.g., notcharging when a battery temperature excesses a threshold value). In someembodiments, the predicted battery demands are generated based onanalyses involving a clustering process and/or a machine learningprocess. For example, the disclosed system collects battery demandinformation (e.g., the number of battery exchanges in the past, batteryreservations, user behavior, etc.) from various sampling stations. Thesystem then performs a clustering process (e.g., by a K-means clusteringprocess) to determine multiple demand clusters. The clusters can becharacterized by both “station” and a “time interval.” For example,Cluster A can represent the battery demand for Station X during 1 a.m.to 4 a.m., Cluster B can represent the battery demand for Station Yduring 5 p.m. to 6 p.m., and Cluster C can represent the battery demandfor Station Z during 2 a.m. to 4 a.m.

In some embodiments, the disclosed system can perform a “just-in-time”charging process. In such embodiments, the system charges a battery in arelatively slow way (e.g., using lower current for a longer period oftime or charging the battery during a time period that charging power isless expensive) until a battery demand is confirmed (e.g., a userreservation or a predicted demand), so that the battery could be fullycharged before it is provided to the user). Charging with lower currentcan result in better battery health and/or longer battery life. Once thebattery demand is confirmed, the system can then charge the battery in arelatively fast fashion (e.g., using higher current for a shorter periodof time), so as to meet the battery demand. When the confirmed batterydemand is a predicted demand, the system can only charge the batteriesto meet that demand. For example, Rule B needs one hour to complete acharging cycle from 20% FCC to 95% FCC and is set as a default chargingrule for battery exchange station A. In some embodiments, if the nextconfirmed battery demand at the battery exchange station A is apredicted demand occurring in 4 hours later, then the system can switchto Rule A to slowly charge the batteries so as to keep the batteryhealthy.

In some embodiments, the disclosed system (e.g., a server) can perform asimulation for a new or an updated battery charging rule, such that astation system can globally or locally determine whether to implementthe new or updated battery charging rule. For example, the system candetermine that a first battery exchange station was turned offline forregular maintenance. The system then generates an updated batterycharging plan (which can include multiple charging rules) for a secondbattery exchange station close to the first battery exchange station.For example, the system determines that turning the first batteryexchange station offline results in an increase of the battery demandfor the second battery exchange station. Accordingly, the system sendsan updated battery charging plan to the second battery exchange station.

After receiving the updated battery charging plan, the second batteryexchange station can perform a simulation for the updated batterycharging plan. The simulation is performed as a background process thatdoes not substantially interfere with the implementation of an existingbattery management plan. In some embodiments, the simulation includessimulating a charging process for a battery positioned in the secondbattery exchange station, based on the updated battery charging plan. Insome embodiments, the simulation includes simulating whetherimplementing the updated battery charging plan can generate a sufficientnumber of charged batteries to meet the actual demand. For example, dueto the expected demand increase, the updated battery charging planrequests the second battery station to charge its batteries at anincreased charging rate faster than a normal rate (which is used is theexisting battery charging plan). After a period of time (e.g., 12hours), the simulation result is generated (e.g., charging at theincreased charging rate results in a 5-degree-Celsius temperatureincrease for the whole station). The simulation result is then comparedto the actual demand. For example, the actual demand indicates thatusing the normal rate to charge the batteries still meets the actualdemand in the past 12 hours (e.g., there was no user waiting forreserved batteries). In such embodiments, the second battery exchangestation can determine not to implement the updated battery chargingplan.

In some embodiments, the candidate charging rules can be determinedbased on economic or financial conditions (e.g., costs or expensesassociated with charging, such as fees for electricity used to charging,rental fees for placing a device-exchange station on a land, etc.). Forexample, the disclosed system can have a set of candidate charging rulesthat applies to batteries located in an area where charging cost variesfrom time to time (e.g., to charge batteries only at a discounted rate),and have another set of candidate charging rules that applies tobatteries located in an area where charging cost remains constant (e.g.,able to charge batteries at all time).

In some embodiments, the candidate charging rules can be determinedbased on the battery reference information (examples are discussed indetail below), such as the number of battery charge cycles, healthindex, cell type of the batteries, etc. For example, if the systemdetermines that a battery is new (e.g., with a new cell type orpackaging mechanism), the system may choose a charging rule with ahigher charging current (e.g., since the battery is new, the highercharging current can charge the battery faster without significantlydegrading the battery).

In some embodiments, the candidate charging rules can be determinedbased on a combination of the various factors discussed above. In someembodiments, the disclosed system can generate a default charging rulefor a battery exchange station to follow (i.e., a battery exchangestation will charge all batteries positioned therein based on thisdefault charging rule). Because the batteries located at the samebattery location may have some factors in common (e.g., sameenvironmental condition, battery demands, charging cost, etc.), it canbe advantageous (e.g., to save computing resources) for the system toassign the same charging rules to the batteries located in the samebattery exchange station. In some embodiments, the assigned chargingrules can be further adjusted based on battery-specific information(e.g., to change the assigned default rule based on the characteristicof an inserted battery). In some embodiments, the charging rule can beset according to several factors/conditions with weightings that neednot correspond to a condition that is named/understood orcontrolled/supervised by an operator. In such embodiments, the chargingrule can be a series of conditional determinations and may not look likethe characteristic curves/lines shown in FIGS. 5A-5C.

In some embodiments, the candidate charging rules can be stored and/ormaintained by a server. In such embodiments, the server can send ordispatch updated charging rules or commands to battery exchange stationsperiodically (e.g., a command such as “to charge the battery at Slot 2with 200 mA for 10 minutes”). In some embodiments, each battery exchangestation can store or maintain a set of default battery charging rules tocharge the batteries positioned therein and the set of default batterycharging rules could be updated by the server periodically (e.g., daily,weekly, quarterly, etc.).

In some embodiments, when a user inserts a battery into a battery slotof a battery exchange station (namely, a battery exchange at the batteryexchange station), the present system (e.g., a battery exchange stationor a combination of one or more battery exchange stations and a server)detects the existence of the inserted battery and then initiates ananalysis process. The system can start by pulling battery informationassociated with the inserted battery from a memory attached to theinserted battery. The system then compares the battery information fromthe inserted battery with the generated characteristics/patterns (e.g.,the “reference information”) to see if there is a match (or asubstantive match). If so, the system can accordingly generate acustomized charging rule (or select one from candidate charging rules)for the inserted battery to achieve a predetermined objective (e.g.,increase/maximize battery performance or life span, minimize chargingexpenses, meet certain predicted demand, etc.) or to meet the assigneddemand while achieving one of the predetermined objectives. If not, thesystem can generate a customized charging rule based on default rules(e.g., identify a closest reference based on the inserted battery'smanufacturing information; identify a closest reference based on theinserted battery's usage information; etc.). By this arrangement, thepresent system can effectively provide suitable, customized chargingrules for each inserted battery and accordingly enhance overall systemefficiency.

Another aspect of the present disclosure is to provide a batterycharging rule in a real-time (e.g., milliseconds to seconds) or nearreal-time (e.g., minutes to hours) manner. For example, when a userpositions a battery in a battery exchange station, the present systemcan immediately provide a suitable charging rule for that battery. Insome embodiments, the system can further adjust the charging rule basedon other factors such as a predicted demand of battery, charging cost,user requests/reservations, environmental conditions, future or currentevents, etc.

For example, the system may accelerate a charging process (e.g., byusing a faster charging process with a higher charging rate or chargingvoltage) at least because it expects a large battery demand in two hoursbased on user's reservations for batteries. As another example, thesystem can delay a charging process (e.g., by using/selecting a slowercharging rule/profile with a lower charging rate or charging voltage)because there is no immediately need to complete the charging process(e.g., it's in the middle of the night and the system does not expectany immediate battery demand) or because doing so may lower chargingexpenses (e.g., a power source offers a lower rate during off-peakhours). In some embodiments, for example, the system can prioritizeavailable batteries in a station based on their SoCs. The system canthen determine how to charge these batteries based on thecharacteristics of the batteries (e.g., the characteristics can berepresented by charging rules). For example, the system can only chargebatteries in a certain SoC range (e.g., 50-80%). For example, assumethat it is 10 a.m. now and a predicted demand shows that there will be 4battery exchanges in Station ST1 at 8 p.m. and there is no predictedbattery demand from now to 8 p.m. Station ST1 now has 4 batteries withinthe 50-80% SoC range. It takes 2 hours for Station ST1 to prepare/chargethese 4 batteries to reach an SoC threshold (e.g., 90%). In thisexample, Station ST1 can plan to start charging these batteries at 6p.m. Accordingly, the present disclosure is capable of providingsuitable charging plans (e.g., based on charging rules and predicteddemands) for a battery exchange service provider to achieve variousgoals (e.g., customer satisfaction, minimize overall charging expenses,etc.).

This disclosure describes systems and methods designed to providecustomized battery charging rules in a real-time or near real-timemanner. Various embodiments may provide one or more of the followingtechnological improvements: (1) efficient real-time or near real-timebattery charging rules ready for a battery exchange station to follow;(2) ability to effectively increase/maximize battery life spans andperformances; (3) ability to enable an operator to set up desirablebattery charging rules based on multiple factors; and (4) ability toprovide enhanced user experiences by offering a satisfying batteryexperience in an energy-efficient fashion.

In the following description, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of embodiments of the present technology. It will beapparent, however, that embodiments of the present technology may bepracticed without some of these specific details.

FIG. 1 is a schematic diagram illustrating a system 100 in accordancewith embodiments of the disclosed technology. The system 100 isconfigured to (1) collect information from multiple sampling batteries101 (shown as 101A-C in FIG. 1); (2) generate a plurality of chargingrules based on the collected information; and (3) based on the chargingrules and predicted battery demand, generate charging plans for aplurality of battery-exchange stations (the charging plans include“battery-specific” charging commands for the station to implement). Insome embodiments, the sampling batteries 101 can be selected from all ofthe batteries owned or managed by an operator of the system 100. Thesystem 100 includes a server 103, a database 105 coupled to the server103, and a battery exchange station 107. As shown, the battery exchangestation 107 can communicate with the server 103 via a wired or wirelesscommunication network 109. Each of the sampling batteries 101 includes abattery memory 113 (shown as 113A-C in FIG. 1). The battery memory 113is configured to store and record battery information associated withthe corresponding sampling battery 101. In some embodiments, the batterymemory 113 can be coupled to a controller (e.g., a control chip, aprocessor, etc., not shown in FIG. 1) attached to the sampling battery101. The controller can manage the battery information stored in thebattery memory 113.

As shown in FIG. 1, the server 103 is configured to (1) collect batteryinformation from the battery memory 113A through the battery exchangestation 107 via the network 109; (2) generate a plurality of chargingrules based on the collected information; and (3) based on the chargingrules and predicted battery demand, generate a charging plan for thebattery exchange station 107. In some embodiments, the server 103 candirectly receive battery information from the battery memory 113B viathe network 109. The server 103 can also receive battery informationfrom the battery memory 113C through a mobile device 111 (e.g., abattery user's smartphone that has an app configured to manage thesampling battery 101C) via the network 109. After collecting the batteryinformation, the server 103 can analyze the collected batteryinformation to determine or identify battery characteristics or patternsthat can be used as reference information to select charging rules fromthe database 105 or to generate customized battery charging rules. Insome embodiments, the server 103 can receive battery information via avehicle (e.g., via a vehicle controller that monitors the batterypositioned therein). In some embodiments, the server 103 can receivebattery information via a charging device (e.g., a charger that enablesa user to charge a battery by household receptacles). Embodiments of theserver 103 are discussed in detail below with reference to FIG. 4.

In some embodiments, the server 103 can manage multiple battery-exchangestations 107 based on demand information and the SoCs of the batteriesin each of the battery-exchange stations 107. The server 103 candetermine a charging plan (and generate charging commands) for each ofthe exchangeable energy storage devices based on the charging rule.

For example, assume the battery-exchange station 107 has 6 batteriestherein (batteries B1-B6). Batteries B1-B6 have SoCs as follows: 92%,90%, 72%, 65%, 45%, and 30%, respectively. In some embodiments, toprovide a satisfying user experience, the system 100 can set a SoCthreshold (e.g., 90% SoC or an adjustable threshold between 85% and 95%SoC) so that only batteries that exceed this threshold can be regardedas batteries that can be exchanged or ready to be picked up by a user.In some embodiments, each of the batteries B1-B6 can have a priorityvalue (e.g., to determine which battery is to be exchanged prior to therest). For example, the priority values of the batteries B1-B6 can beassigned as “1,” “2,” “3,” “4,” “5,” and “6” according to the SoC (andother characteristics) of each battery. In some embodiments, thebatteries B1-B6 can be categorized into two groups while keeping thepriority values, “ready to be picked up” (batteries B1 and B2 for havingSoC more than 90%) and “not ready” (batteries B3-B6 for having SoC lessthan 90%). In some embodiments, there can be a third group, such as“locked batteries,” which can include batteries that need to bemaintained or replaced.

In one example, assume that it takes about 2.5 hours to charge a batteryfrom zero SoC to 90% SoC. The system 100 can get demand information(e.g., predicted battery demands) for at least the next two hours (toallow enough time to charge batteries B1-B6). In other words, thedetermination of a charging plan for the battery exchange station 107 isbased on the predicted demand of the batteries and the required time forfully charging a battery.

Assume that the predicted demand for the next hour is 2 batteries, andthe predicted demand for the hour after the next hour is 4 batteries.Therefore, the sever 103 of the system 100 can select the charging rulesfor the batteries B1-B6 based on the demand information. In thisexample, the system 100 can determine to (1) maintain the SoCs ofbatteries B1 and B2; (2) charge batteries B3 and B4 based on arelatively slow charging rule (e.g., their SoCs are close to the 90%threshold; using the relatively slow charging process can decrease heatgenerated during the process, which is beneficial for battery lives);and (3) charge batteries B5 and B6 based on a relatively fast chargingrule (e.g., to meet the predicted demand).

The determination of whether to charge the batteries in the“ready-to-be-picked-up” group is based on available power of thebattery-exchange station 107. Also, the available power can also be afactor to determine charging rates of the batteries. In one example, thesystem 100 can determine to (a) charge batteries B1 and B2 based on acharging rule following which to charge batteries at a constant voltagewhen the SoC of these batteries are over the SoC threshold; (b) chargebatteries B3 and B4 based on a relatively slow charging rule (e.g.,charge the batteries at a charging rate of 0.3C when the SoC of thebatteries are under 90%, where “C” means the “C-Rate” for batterycharging); e.g., the capacity of a battery is commonly rated at “1C,”meaning that a fully charged battery rated at 1A-hr should provide 1Afor one hour); and (c) charge batteries B5 and B6 with a relatively fastcharging rule (e.g., charge the batteries at a charging rate of 0.7Cwhen the SoCs of batteries are under 70%). When the available power islimited in this battery-exchange station 107, the server 103 of thesystem 100 may generate charging commands based on the selected chargerules and available power of the battery exchange station 107, so thatthe batteries B5 and B6 may be charged in a rate lower than 0.7C, andthe estimated time to fully charge these two batteries can be longer.

In one aspect, the server 103 of the system 100 can send a package ofcharging commands (e.g., the items (a), (b) and (c) for batteries B1-B6described above) generated based on a set of charging rules stored inthe server 103 to the battery-exchange station 107. By this arrangement,the system 100 can provide various charging schemes to meet thepredicted demands, without unnecessarily sacrificing of batterydurability (e.g., in the foregoing example, the durability of batteriesB5 and B6 are sacrificed for meeting the predicted demand somehow).

In some embodiments, the disclosed technology enables the server 103 tomanage a plurality of batteries in various battery-exchange stations 107by (1) periodically or frequently generating charging commands for thesebatteries based on the charging rules selected for each of the batteriescurrently position on the battery exchange station 107; and (2) sendingthe generated commands to the battery-exchange stations 107. Forexample, the system 100 can select new charging rule to generate newcharging commands for each of the batteries currently positioned in thebattery exchange station 107 in response to a triggering event such asan exchange of the exchangeable energy storage devices positioned in thedevice-exchange station 107, a change to the available power, a changeto demand information, or a reservation for the exchangeable energystorage devices positioned in the device-exchange station 107. Forexample, if that a battery exchange occurs at the battery-exchangestation 107 before the server 103 makes its prediction, then thebatteries B1 and B2 are provided to a user according to their setpriorities (i.e., the priority values assigned), and two batteries withSoCs lower than 50% are returned back to the battery exchange station107. The demand information remains the same but the situation of theSoCs of the batteries are different. As a result, the server 103 of thesystem 100 updates the whole charging plan in response to this batteryexchange, which may include (1) selecting charging rules for everybattery in the battery exchange station 107 and (2) generating newcharging commands for the batteries based on the updated charging rulesrespectively. Embodiments are discussed in detail below.

For example, an associated method can include, for example (S1)calculating the number of batteries in multiple stations (e.g., similarto the station 107); (S2) determining priorities of the batteries (e.g.,based on SoCs); and (S3) grouping the batteries based on the priorities.For example, the batteries can be divided into three groups, first,second and third groups. The first group has batteries with 90% or moreSoC, the second group has 90% or lower SoC, and a third group has“locked,” “non-chargeable” or “non-exchangeable” batteries (due tomaintenance/replacement schedules). Using the above-mentioned batteriesB1-B6 (with SoCs: 92%, 90%, 72%, 65%, 45%, and 30%) as an example, B1and B2 are assigned to the first group, and B3-B6 are assigned to thesecond group. In this example, no batteries are assigned to the thirdgroup. B1 has the highest priority, and B6 has the lowest priority. Insome examples where there are other significant differences oncharacteristics of batteries (e.g., age of batteries or cell type of thebatteries), the priority can also be adjusted based on thesecharacteristics.

The associated method can further include: (S4) receiving a batterydemand prediction in a time interval (e.g., the next two hours or othertime intervals in other embodiments). The time interval is determinedbased on an average of charging time required by the batteries (e.g.,two hours). For example, the battery demand prediction for the next houris “2” (i.e., two battery exchanges are expected), and the batterydemand prediction is “4” during the hour after the next hour. In thisembodiment, battery B1 and B2 can be used to meet the next hour demand,and batteries B3-B6 can be prepared/charged to meet the demand for thehour after the next hour.

The associated method can further include: (S5) determining availablepower to charge the batteries (e.g., available power that thebattery-exchange station 107 can utilize, an expected power outage,etc.); (S6) based on the priority, selecting a battery to be charged;and (S7) determining/selecting a charging rule for each of thebatteries.

Assume that one of the charging rules (namely, the charging rule CR1)include that (a) for batteries with SoC higher than 95% (including 95%),using a “slowest” charging process (e.g., 0.2C); and (b) for batterieswith SoC lower than 95%, using a “faster” charging process (e.g., 0.7C).The charging rule CR1 can be chosen when it is required to meet apredicted demand (e.g., unless to meet an urgent demand, it is preferredto use the slower charging process for better battery life expectancy).

Also, another charging rule (namely, the charging rule CR2) can includethat (a) charging batteries with SoC higher than 90% (including 90%) ata first charging rate (e.g., 0.2C, the “slowest” charging process); (b)charging batteries with SoC from 60% to 90% at a second charging rate(e.g., 0.4C, a “slower” charging process); and (c) charging batterieswith SoC lower than 60% at a third charging rate (e.g., 0.7C, the“faster” charging process). In our example, batteries B5 and B6 arechosen to be charged based on the charging rule CR1 (e.g., it willprobably take two hours to fully charge batteries B5 and B6). BatteriesB1 and B2 can be charged based on the charging rule CR2 since SoCs ofthe batteries B1 and B2 exceed the SoC threshold (note that thebatteries B1 and B2 can also be charged based on the charging rule CR1in this example). Batteries B3 and B4 can also be charged based on thecharging rule CR2, since it is easy to meet the demand assigned tobatteries B3 and B4 using the charging rule CR2.

In some embodiments, the associated method can further include: (S8)determining charging rates (e.g., charging rate “C” discussed above)based on the characteristics of the batteries (e.g., a currenttemperature, SoC, etc.). This step can be considered as a “fine-tuning”of the charging rules. For example, the method can include using SoC todetermine the charging rates for each of the batteries. For example,batteries B1 and B2 (with SoC higher than 90%) can be charged with 0.2C,the “slowest” charging process in reference with the charging rule CR2that is chosen for batteries B1 and B2 in step (S7). Batteries B3 and B4(SoC in the range of 89-60%) at the rate of “0.4C.” Batteries B5 and B6(with SoC in the range of 50-0%) at the rate of “0.7C” with reference tothe charging rule CR1. In some embodiments, the charging rules furtherinclude conditions regarding the temperature of batteries. For example,in condition (c) of the charging rule CR2, the batteries with SoC lowerthan 60% are charged with the third charging rate (e.g., 0.7C), but ifthe temperature of the batteries is over a certain temperature threshold(e.g., 50 degree Celsius), the batteries would be charged with thesecond charging rate (e.g., 0.4C), so as to prevent the batteries fromoverheating, which may not only damage the batteries, but also affectthe user experience.

In some embodiments, the associated method can further include: (S9)adjusting charging rates (e.g., charging rate “C” discussed above) basedon other factors such as available power to charge (e.g., as discussedin above-mentioned step S5). In some embodiments, when there is anexpected power outage and the device-change station 107 only has limitedpower to charge the batteries, it can only charge batteries in a certainSoC range (e.g., SoC 50-80%). For example, only batteries B3 and B4 arecharged. As another example, there can be only limited power suppliedfrom mains electricity so that the device-exchange station is notcapable of charging all the batteries positioned therein based on thecorresponding charging rules. Also, there can be multiple batteryexchange station units (e.g., a modular design that enables easy, quickexpansion) at the same location that need to share available power. Insome instances, the power can be supplied by renewable power sources(e.g., solar panels) and the power provided by these sources may varywith time.

In some embodiments, the associated method can further include: (S10)generating charging commands for each of the batteries (e.g., batteriesB1-B6) based on the determined charging rules and theadjusted/determined charging rates. The server 103 can then send thegenerated charging commands to each of the device-exchange stations 107.The device-exchange stations 107 can then implement the chargingcommands. In other words, each of the charging commands includes theexact value of adjusted/determined charging rate so that thedevice-exchange stations 107 can charge the batteries positioned thereinby the corresponding charging commands. The server 103 can continuouslymonitor the status of the batteries (SoC, temperature, etc.) and updatethe charging commands according to the charging rules that correspond tothe batteries, respectively.

The foregoing embodiments (e.g., steps S1-S10) discuss how to form“charging plans” for device-exchange stations 107 based on predicteddemands for exchangeable energy storage devices. The server 103 can formcharging plans for each of the device-exchange stations connected to theserver 103, respectively (e.g., the device-exchange station 107). Asdiscussed, the “overall charging plan” can represent how the server 103can manage (e.g., charge) all the connected device-exchange stations 107and the energy storage devices therein, so as to meet the demand fromusers while keeping the energy storage devices healthy and durable. The“charging plan” for each of the device-exchange station can include“charging rules” to be selected and assigned for energy storage devicesin the device-exchange station 107. The charging rules describe detailsof charging an energy storage device (and a corresponding objective thatcan be achieved thereby). Also, “charging commands” for each of energystorage devices positioned in the device-exchange stations 107 aregenerated based on the assigned/selected “charging rules” and can beupdated frequently based on current conditions of the battery (e.g.,SoC, temperature, etc.) and the assigned/selected charging rules.

The database 105 can store information associated with the presentdisclosure (e.g., demand information, information collected by theserver 103, information analyzed by the server 103, informationgenerated by the server 103 (e.g., charging rules, charging plans, orcharging commands), reference information, user account information,user battery plans, user histories, user behavior, user driving/ridinghabits, environmental conditions, event information, etc.). In someembodiments, the database 105 can be a publicly accessible database(e.g., weather forecast database, travel alert database, trafficinformation database, location service database, map database, etc.)maintained by government or private entities. In some embodiments, thedatabase 105 can be a private database that provides proprietaryinformation (e.g., user account, user credit history, user subscriptioninformation, etc.).

The network 109 can be a local area network (LAN) or a wide area network(WAN), but it can also be other wired or wireless networks. The network109 can be the Internet or some other public or private network. Thebattery exchange station 107 or the mobile device 111 can be connectedto the network 109 through a network interface (e.g., by wired orwireless communication). The server 103 can be coupled to the database105 via any kind of local, wide area, wired, or wireless network,including the network 109 or a separate public or private network. Insome embodiments, the network 109 includes a secured network that isused by a private entity (e.g., a company, etc.).

In some embodiments, the battery exchange station 107 can be configuredto collect battery information from the sampling batteries 101 andperform the analysis discussed above. In such embodiments, the batteryexchange station 107 can analyze the collected battery information todetermine or identify battery characteristics or patterns that can beused as reference information for generating customized battery chargingrules. Such reference information can be stored locally (e.g., in thebattery exchange station 107) or can be transmitted or uploaded to theserver 103. Embodiments of the battery exchange station 107 arediscussed in detail below with reference to FIGS. 2 and 3.

FIG. 2 is a schematic diagram illustrating a system 200 in accordancewith embodiments of the disclosed technology. The system 200 isconfigured to determine a customized battery charging rule or profilefor an exchangeable battery 201. The system 200 includes a server 203, adatabase 205, and a battery exchange station 207. The server 203,database 205, and the battery exchange station 207 can communicate withone another via a network 209. As shown, the battery exchange station207 includes (i) a display 215 configured to interact with a user, and(ii) a battery rack 219 having eight battery slots 217 a-h configured toaccommodate batteries to be charged.

During operation, there are only six battery slots (e.g., slots 217 a,217 b, 217 d, 217 e, 217 f, and 217 h) occupied by batteries, and theremaining two slots (e.g., slots 217 c and 217 g) are reserved for auser to insert a battery to be exchanged (e.g., low power batteries).The batteries B1-B6 discussed above or the sampling batteries 101A-101Cdiscussed above with reference to FIG. 1 can be positioned in thesebattery slots 217 a-h, respectively. In some embodiments, the batteryexchange station 207 can have different arrangements such as differentnumbers of racks, displays, and/or slots. In some embodiments, thebattery exchange station 207 can include modular components (e.g.,modular racks, modular displays, etc.) that enable an operator toconveniently install or expand the battery exchange station 207. Thebattery exchange station 207 can be electrically coupled to one or morepower sources (e.g., power grid, power lines, power storage, powerstation/substations, solar cells, wind-powered generators, fuel poweredgenerators, etc.) to receive power to charge the batteries positionedtherein and to perform other operations (e.g., to communicate with theserver 203). In some embodiments, a user can remove a battery from thebattery exchange station 207, without inserting one beforehand. In someembodiments, the battery exchange station 207 can have a lockingmechanism for securing the batteries positioned therein. In someembodiments, the battery exchange station 207 can be implemented withoutthe locking mechanism.

As discussed above with reference to FIG. 1, a set of referenceinformation can be generated based on battery information collected fromthe multiple sampling batteries 101. In some embodiments, the referenceinformation can be stored in the database 205 or the server 203. A usercan insert an exchangeable battery 201 (which includes a battery memory213 configured to store various types of battery information discussedabove) into an empty battery slot (e.g., slot 217 c, as shown in FIG. 2)of the battery exchange station 207. The battery exchange station 207can collect the battery information and transmit the same to the server203. The server 203 analyzes the collected battery information andcompares it with the stored reference information. The sever 203accordingly generates a customized battery charging rule for theexchangeable battery 201 to achieve an objective.

In some embodiments, the server 203 can identify one or morecharacteristics of the exchangeable battery 201 and generates thecustomized battery charging rule by finding a match (or a general match)from the reference information. In some embodiments, the server 103 canfirst identify a previous charging rule for the exchangeable battery 201(e.g., from the collected information) and then adjust it based on thereference information so as to generate the customized battery chargingrule for the exchangeable battery 201. For example, a recentanalysis/study (which can be part of the reference information) maysuggest that the exchangeable battery 201 can perform better if it ischarged at a specific temperature for a period of time. The server 103can accordingly adjust the previous charging rule to generate an updatedcharging rule.

In some embodiments, the reference information can be stored in thebattery exchange station 207. In such embodiments, the battery exchangestation 207 can analyze/compare the collected information and thereference information to generate the customized charging rule. Thebattery exchange station 207 can also locally store/manage a set ofgenerated customized charging rules for future use. In some embodiments,the battery exchange station 207 can upload the generated customizedcharging rules to the server 203 for future use.

FIG. 3 is a schematic diagram illustrating a (charging) station system300 in accordance with embodiments of the disclosed technology. Asshown, the station system 300 includes a processor 301, a memory 303, auser interface 305, a communication component 307, a battery managementcomponent 309, one or more sensors 311, a storage component 313, and acharging component 315 coupled to multiple battery slots 317 a-n. Theprocessor 301 is configured to interact with the memory 303 and othercomponents (e.g., components 305-317) in the station system 300. Thememory 303 is coupled to the processor 301 and is configured to storeinstructions for controlling other components or other information inthe station system 300.

The user interface 305 is configured to interact with a user (e.g.,receiving a user input and presenting information to the user). In someembodiments, the user interface 305 can be implemented as a touchscreendisplay. In other embodiments, the user interface 305 can include othersuitable user interface devices. The storage component 313 is configuredto store, temporarily or permanently, information, data, files, orsignals associated with the station system 300 (e.g., informationmeasured by the sensors 313, information collected by the batteries 317a-n, reference information, charging instructions, user information,etc.).

The communication component 307 (e.g., devices suitable forcommunicating under Bluetooth, infrared, cellular, IEEE 802.11, etc.) isconfigured to communicate with other systems, such as a vehicle 31(e.g., an electric vehicle that uses the exchangeable battery 201 as itspower source), a mobile device 32 (e.g., a battery user's smartphonethat has an app configured to manage the exchangeable battery 201), aserver 33 (e.g., the server 103, 203 or the server system 400 to bediscussed below with reference to FIG. 4), other station stations,and/or other devices.

The battery management component 309 is configured to collect batteryinformation from various sources and to analyze the collectedinformation. For example, the battery management component 309 cancollect information regarding the batteries positioned in the batteryslots 317 a-n, information regarding the station system 300, informationregarding one or more power sources 34, information regarding a user(e.g., received from the mobile device 32 via the communicationcomponent 307), and/or information regarding the vehicle 31. In someembodiments, the battery management component 309 can transmit or uploadthe collected information to the server 33 for further analysis orprocess. After receiving the battery information, the server 33 cananalyze the received battery information and compare it to the referenceinformation so as to generate a customized battery charging rule forbatteries to achieve predetermined objectives.

In some embodiments, the battery management component 309 can manage thebatteries positioned in the batter slots 317 based on instructions fromthe server 33 (which can function in the ways similar to the server 103,303 and the server system 400 to be discussed in detail below withreference to FIG. 4). In some embodiments, the battery managementcomponent 309 can periodically communicate with the server 33 to requestupdated instructions.

In some embodiments, the battery management component 309 can analyzethe collected battery information associated with a battery inserted inone of the battery slots 317 and compare the collected batteryinformation with the reference information. The battery managementcomponent 309 can accordingly generate a customized battery chargingrule for the inserted battery based on the comparison. In someembodiments, the customized battery charging rule can be determined bythe server 33.

The charging component 315 is configured to control a charging processfor each of the batteries positioned in the battery slots 317 a-n. Thebattery slots 317 a-n are configured to accommodate and charge thebatteries positioned and/or locked therein. The charging component 315receives power from the power sources 34 and then uses the power tocharge the batteries positioned in the battery slots 317 a-n, based onpredetermined customized charging rules, either received from the server33 or generated by the battery management component 309.

In some embodiments, the customized charging rules can be adjusted basedon a battery demand prediction generated by the server 33 (e.g., thebattery demand prediction can be generated based on predicted userbehavior, station characteristics, events close to a battery exchangestation, etc.). For example, the station system 300 can delay toimplement a battery charging rule if it determines that there is nosufficient power from the power sources 34 to implement the batterycharging rule.

The sensors 311 are configured to measure information associated withthe station system 300 (e.g., working temperature, environmentalconditions, power connection, network connection, etc.). The sensors 311can also be configured to monitor the batteries positioned in thebattery slots 317 a-n. The measured information can be sent to thebattery management component 309 and/or the server 33 for furtheranalysis. In some embodiments, the measured information can be includedin the reference information that is used to generate the customizedcharging rules. For example, the customized charging rules can varydepending on the temperature surrounding the station system 300 or thetemperatures at the battery slots 317.

FIG. 4 is a schematic diagram illustrating a server system 400 inaccordance with embodiments of the disclosed technology. The serversystem 400 is configured to collect information associated with multiplebatteries that can be deployed or managed by the server system 400. Theserver system 400 is also configured to analyze the collectedinformation and generate, based on the analysis, a customized batterycharging rule for a client station 40 to control a charging processtherein. In some embodiments, the client station 40 can be implementedas the battery exchange station 107 or 207 discussed above. In otherembodiments, the client station 40 can be implemented as other suitableclient devices. The server 33, 103 or 203 described above can have astructure, components, and/or elements similar to those of the serversystem 400.

As shown in FIG. 4, the server system 400 includes a processor 401, amemory 403, input/output (I/O) devices 405, a storage component 407, acharging rule analysis component 409, a power source analysis component411, a station analysis component 413, a user behavior analysiscomponent 417, a vehicle analysis component 419, and a communicationcomponent 421. The processor 401 is configured to interact with thememory 403 and other components (e.g., components 405-421) in the serversystem 400.

The I/O devices 405 are configured to communicate with an operator(e.g., receive an input therefrom and/or present information thereto).In some embodiments, the I/O devices 405 can be one component (e.g., atouch screen display). In some embodiments, the I/O devices 405 caninclude an input device (e.g., keyboards, pointing devices, card reader,scanner, camera, etc.) and an output device (e.g., a display, networkcard, speaker, video card, audio card, printer, speakers, or otherexternal device).

The storage component 407 is configured to store, temporarily orpermanently, information, data, files, or signals associated with theserver system 400 (e.g., collected information, reference information,information to be analyzed, analysis results, etc.). In someembodiments, the storage component 407 can be a hard disk drive, flashmemory, or other suitable storage means. The communication component 421is configured to communicate with other systems (e.g., the clientstation 40 or other stations) and other devices (e.g., a mobile devicecarried by a user, a vehicle, etc.).

The charging rule analysis component 409 is configured to collect andstore (e.g., in the storage component 407) battery information to beanalyzed. The collected information can be collected from multiplesampling batteries from various sources (e.g., battery exchangestations, electric vehicles, batteries, user mobile devices, etc.). Thecollected battery information includes, for example, one or more of (1)battery manufacturing information (e.g., battery manufacturers,manufacturing dates, manufacturing batches, manufacturing serialnumbers, hardware versions, firmware versions, cell types, etc.), (2)battery characteristic information (e.g., a battery capacity, a batterydischarging capacity, a suggested battery working temperature, SOH,etc.); (3) battery charging information (e.g., SOC information, acurrent battery temperature, a current cell temperature, a currentcircuit temperature, an error status, a suggested battery chargingtemperature, a suggested battery charging current, a suggested batterycharging voltage, a suggested battery charging cycle, a suggestedbattery charging speed, a suggested battery charging time, etc.); (4)battery usage information (e.g., a battery age, a battery internalresistance, an actual battery charging temperature, an actual batterycharging current, an actual battery charging voltage, an actual batterycharging cycle, an actual battery charging speed, an actual batterycharging time, an actual battery working temperature, an actual batterydischarging time, etc.), and (5) battery identity information (e.g., aunique battery serial number for each deployed battery). After receivingthe collected information, the charging rule analysis component 409 cananalyze the collected information.

Each type of collected information above can be analyzed to identifycharging characteristics/patterns that may affect a battery's chargingprocess. The identified charging characteristics/patterns can be in aform of characteristic curves/lines shown in FIGS. 5A-5C, to bediscussed in detail below). These identified characteristics/patternscan be considered by the charging rule analysis component 409 togenerate a battery charging rule for batteries in the client station 40.

In some embodiments, the charging rule analysis component 409 canprioritize the collected information based on their relative importanceor reliability. For example, the charging rule analysis component 409can use the “battery manufacturer” (or types of battery cells, in otherembodiments) as a primary factor and set other items as secondaryfactors when determining a battery charging rule for the client station40. In such embodiments, the system 400 can identify a charging curve(e.g., as shown in FIGS. 5A-5C, to be discussed in detail below) for theclient station 40 based on the manufacturer of the battery to becharged. The charging rule analysis component 409 can then considerother secondary factors to adjust the identified charging curve.

In some embodiments, the charging rule analysis component 409 can givedifferent types of collected information different weightings. Forexample, the charging rule analysis component 409 can set the weightingsfor the “state of charge,” the “battery charging temperature,” and the“charging current” as 50%, 20%, and 30%. In such embodiments, theidentified characteristics/patterns for each type of collectedinformation can then be combined based on the foregoing weightings. Insome embodiments, the charging rule analysis component 409 can determinewhich types of collected information to be included based on empiricalstudies, results of a machine learning process, and/or system operator'spreference.

In some embodiments, the charging rule analysis component 409 candetermine the priorities or weightings for each type of the collectedinformation based on the reliability of the collected information. Forexample, for information measured and collected from memories coupled tothe batteries, the charging rule analysis can give it higher weightingor priority because the server system 400 considers such information isdirect/internal and thus more reliable than indirect/externalinformation such as environmental conditions (e.g., a weather forecast,an event notice, etc.).

In some embodiments, the charging rule analysis component 409 cancommunicate and work together with other components in the system 400(e.g., components 411-419) to generate a customized battery chargingrule for batteries in the client station 40. In some embodiments,however, the system 400 can operate without components 411-419.

The power source analysis component 411 is configured to analyze thestatus (e.g., reliability, stability, continuity, etc.) of one or morepower sources that are used to power the client station 40 for chargingthe batteries therein. For example, the power source analysis component411 can determine that a power source used to supply power to the clientstation 40 will be interrupted during 1 a.m. to 3 a.m. on a particulardate, and then the power source analysis component 411 can accordinglyadjust a charging rule. In some embodiments, the power source analysiscomponent 411 can also consider the cost for charging in different timeperiods. For example, the power source analysis component 411 candetermine that the charging cost from a power source is reduced duringoff-peak hours. The power source analysis component 411 can determinewhether it is feasible for the client station 40 to charge its batteriesduring the off-peak hours. If so, the power source analysis component411 can adjust the charging rule to reduce charging costs.

The station analysis component 413 is configured to categorize themultiple battery exchange stations into various types and identifyrepresentative characteristics/patterns for each type, such that thecharging rule analysis component 409 can use such information as basisfor its analysis. For example, the station analysis component 413 cananalyze the collected information and divide the multiple batteryexchange stations into various types based on their battery demands.Based on these types, the charging rule analysis component 409 and thestation analysis component 413 can quickly determine a suitable batterycharging rule, especially in cases where the collected information isinsufficient for the charging rule analysis component 409 to perform anormal analysis.

Similar to the station analysis component 413, the user behavioranalysis component 417, and the vehicle analysis component 419 are alsoconfigured to categorize the user behavior and vehicles powered by thebatteries, respectively, into various types and identify representativecharacteristics/patterns for each type. The user behavior analysiscomponent 417 can receive a reservation for a battery from a smartphoneor other computing device associated with the server and can categorizethe user behavior based on how they exchange and/or use the batteries.For example, a user can be very demanding on battery performance (e.g.,a professional racer). As another example, another user may only usebattery to power its vehicle for daily errands (e.g., picking upchildren or grocery shopping). If a user reserves a battery at theclient station 40, the client station 40 then provides informationassociated with the reservation to the server system 400. The serversystem 400 can then determine the type/category of the user who made thereservation and accordingly adjust the battery charging rule for theclient station 40. In some embodiments, such adjustment can be made bythe client station 40.

The vehicle analysis component 419 can categorize the types of vehiclesthat users are planning to operate. For each type of vehicles, thevehicle analysis component 419 can determine which types of batterieswork best for each type of vehicles. For example, the vehicle analysiscomponent 419 can determine that an electric scooter works best with aspecific type of battery after a particular charging process. In suchembodiments, the vehicle analysis component 419 can work with (e.g.,provide details to) the demand analysis component 409 to adjust thebattery demand prediction (and the corresponding charging instructions),if the server system 400 receives related vehicle information. In someembodiments, such information can be found in the user profiles oraccount information. In other embodiments, such vehicle information canbe provided by the client station 40 to the server system 400.

In some embodiments, the server system 400 can generate a customizedbattery charging rule for the batteries in the client station 40 in areal-time or near real-time manner. In such embodiments, the serversystem 400 monitors the status of the client station 40. Once there is achange (e.g., a user just removed two fully-charged batteries and lefttwo empty ones at the client station 40) or a potential change (e.g., auser makes a reservation to exchange batteries at the client station 40)that may affect the charging process of the client station 40, theserver system 400 can perform the analysis mentioned above and generatean updated battery charging rule for the client station 40 to follow. Insome embodiments, the change or potential change can be transmitted tothe server system 400 from a mobile device (e.g., a user uses an appinstalled thereon to make a battery reservation), another server (e.g.,a web-service server associated with an app used by a user), and/or theclient station 40.

FIGS. 5A-5C are schematic diagrams illustrating battery chargingcharacteristics or patterns in accordance with embodiments of thedisclosed technology. FIG. 5A illustrates “step-charge” battery chargingprofiles (or rules) in accordance with embodiments of the disclosedtechnology. As shown in FIG. 5A, a battery charging profile 51 can beillustrated based on the relationship between the state of charge (SOC)and the charging current of a battery (or a type of battery). Thebattery charging profiles 51, 52, and 53 are different types of“step-charge” profiles. When charging a battery based on this type ofprofile, the battery is charged by different currents in differentcharging stages. For example, the battery charging profile 51 refers toa charging process wherein the charging current decreases when thebattery is close to its full charge capacity. The battery chargingprofile 52 refers to a charging process having a first portion 52A and asecond portion 52B. In the first portion 52A, the charging currentremains constant. In the second portion 52B, the charging voltageremains constant (and accordingly the charging current varies). In someembodiments, a charging profile can include two or more stages. Forexample, the battery charging profile 53 refers to a charging processhaving a first portion 53A, a second portion 53B, and a third portion53C. In the first portion 53A and the second portion 53B, the chargingcurrents remain constant. In the third portion 53C, the charging voltageremains constant (and accordingly the charging current varies).

Selecting different charging profiles or rules results in differentchanging commands. For example, if the system determines that thecharging process for battery X is governed by the battery chargingprofile 51 and assume that the current SoC of battery X is 80% SoC, thenthe system can generate a corresponding charging command (e.g., tocharge battery X at charging current C1 (e.g., 2 Ampere) shown in FIG.5A or at other voltage). In some embodiments, if the current SoC ofbattery X is 20% SoC, then the system can generate another chargingcommand (e.g., to charge battery X at charging current C2 (e.g., 15Ampere). As a result, battery A can be charged at different rates,varying with its SoC. For example, when its SoC is high, it will becharged by a slower charging process. When its SoC is low, it will becharged by a faster charging process.

In some embodiments, the charging profile can be illustrated orcharacterized by other factors such as a “C-rate.” The “C-rate” can bedefined as a rate at which a battery is charged (or discharged) relativeto its capacity. For example, a battery can have a full capacity of 1000mA-hour. For this battery, a charging rate of 500 mA corresponds to aC-rate of “0.5,” which means, by this charging rate, the battery canincrease 50% of its capacity per hour. In some embodiments, thedisclosed system can use “C-rate” to characterize charging profiles.

In FIGS. 5B and 5C, six two-dimensional characteristic curves (or lines)501A-C and 505A-C are shown. In other embodiments, however, thecharacteristic curves can be three-dimensional or multiple-dimensional,depending on the number of factors to be considered when generating suchcharacteristic curves.

Referring to FIG. 5B, the characteristic curves 501A-C representcharging features for battery A. The charging features are generated(e.g., by a server such as the server system 400 or by a station such asthe station system 300) based on information associated with multiplesampling batteries (e.g., the collected information mentioned above). Insome embodiments, these characteristic curves 501A-C can be comparedwith actual measurements so as to verify and/or enhance the accuracy ofthese curves (e.g., compare the characteristic curve 501A with a curvegenerated by actual measurement from battery A). In such embodiments,the results of the comparison can be used to further adjust thecharacteristic curves 501A-C. In some embodiments, the presenttechnology can use this approach to fine-tune its analysis based onvarious factors, weightings for the factors, algorithms, etc.

As shown in FIG. 5B, the characteristic curve 501A indicates that thebattery to be charged is charged in a “step-charge” fashion. Thecharacteristic curve 501B indicates that the charging temperature of thebattery to be charged should be decreased when the charging timeincreases to achieve a pre-determined objective (e.g., increase/maximizebattery capacity, longest battery life, etc.). The characteristic curve501C indicates that the charging current for the battery to be chargedshould be kept generally the same when charging to achieve thepre-determined objective.

Turning to FIG. 5C, the characteristic curves 505A-C represent chargingfeatures for Battery B. The charging features are generated (e.g., by aserver such as the server system 400 or by a station such as the stationsystem 300) based on information associated with multiple samplingbatteries (e.g., the collected information mentioned above). In someembodiments, these characteristic curves 505A-C can be compared withactual measurements so as to verify and/or enhance the accuracy of thesecurves (e.g., compare the characteristic curve 505A with a curvegenerated by actual measurement from Battery B). In such embodiments,the results of the comparison can be used to further adjust thecharacteristic curves 505A-C. In some embodiments, the presenttechnology can use this approach to fine-tune its analysis based onvarious factors, weightings for the factors, algorithms, etc.

As shown in FIG. 5C, for example, the characteristic curve 505Aindicates that when the SOC increases, the battery exchange stationtemperature should be decreased to achieve a pre-set goal. Thecharacteristic curve 505B indicates that when the SOC increases, thecharging voltage should be decreased “stepwise” to achieve the pre-setgoal. As shown in FIG. 5C, without wishing to be bonded by theory, thecharacteristic curve 505C includes a peak portion 507. The peak portion507 indicates that when the SOC of Battery B reaches certain levels, thecharging current can be increased so as to achieve the pre-set goal.

In some embodiments, the present technology can provide multiple typesof characteristic curves or patterns that can be used as referenceinformation to determine how to charge a particular battery to achievean objective or a goal. In some embodiments, the objective or goal canbe determined based on financial reasons (e.g., to reduce operationexpenses), customer satisfaction (e.g., to provide highest possiblebattery experience to a user), or other suitable factors. In someembodiments, the charging rules/profiles can be represented by one ormore conditions, criteria, and/or parameters (e.g., characteristics ofthe batteries or characteristics of the device-exchange stations) andare not limited to the curves shown in FIGS. 5A-5C.

FIG. 6 is a flowchart illustrating a method 600 in accordance withembodiments of the disclosed technology. The method 600 is configured togenerate a charging rule for an exchangeable battery positioned in abattery-exchange station. The method 600 is also configured to instructthe station to charge the exchangeable battery based on the generatedcharging rule. The method 600 can be implemented (1) by a server (e.g.,the server system 400 discussed above) with a battery exchange station(e.g., the station system 300) or (2) by a battery exchange stationalone. The method 600 starts at block 601 by receiving from a memoryattached to the exchangeable battery (e.g., a battery to be charged), aset of battery information. The battery information includes batterymanufacturing information, battery characteristic information, batterycharging information, and battery usage information.

At block 603, the method 600 continues by analyzing the receivedinformation based on predetermined reference information. In someembodiments, the predetermined reference information is generated basedon information collected from multiple sampling batteries. The samplingbatteries and the exchangeable battery have at least one characteristicin common, and therefore the present technology can use thischaracteristic in common to determine which part of the collectedinformation (and also how much weighting should be assigned thereto) isgoing to be used to determine a charging rule for the exchangeablebattery.

At block 605, the method 600 then determines available power to besupplied to each of the battery exchange station before a target timeperiod. At block 607, a charging rule for the exchangeable battery isgenerated to achieve a pre-determined objective. The charging rule is tobe implemented during a charging period which is before the target timeperiod.

At block 609, the method 600 includes instructing a charging controlcomponent of the battery-exchange station to charge the exchangeablebattery according to the charging rule (e.g., by sending correspondingcharging commands to the battery-exchange station or by sendingcorresponding charging commands to a charging control component from aprocessor of the battery-exchange station). The method 600 then returnsand waits for further instructions.

In some embodiments, the charging rules described therein can becharacterized, determined, defined, predicted, and/or “trained” based onhistorical data collected by the disclosed system and can be furtheradjusted based on updated data (e.g., new battery usage data, new userbehavior data, etc.). In some embodiments, the charging rules can beupdated every day/week/month/season based on the updated data.

FIG. 7 is a flowchart illustrating a method 700 in accordance withembodiments of the disclosed technology. The method 700 is for chargingexchangeable energy storage devices (e.g., batteries) positioned in adevice-exchange station. The method 700 can be implemented by a server(e.g., the server system 400 discussed above). The method 700 starts atblock 701 by receiving demand information for the device-exchangestation. At block 703, the method 700 continues by determining acharging plan for the device-exchange station at least partially basedon a state-of-charge (SoC) of each of the exchangeable energy storagedevices positioned in the device-exchange station, the plurality ofpredicted exchange demands, and an available power of thedevice-exchange station (e.g., from a power source, a power grid, etc.).The charging plan includes at least one charging rule for each of theexchangeable energy storage devices positioned in the device-exchangestation.

At block 705, the method 700 generates a charging command for each ofthe exchangeable energy storage devices based on the charging rule. Atblock 707, the method 700 continues by transmitting the charging commandto the device-exchange station. In some embodiments, the method 700includes periodically updating the charging plan or updating thecharging plan in response to a triggering event. In some embodiments,the triggering event includes an exchange of the exchangeable energystorage devices positioned in the device-exchange station, a change tothe available power, and/or a reservation for the exchangeable energystorage devices positioned in the device-exchange station.

In some embodiments, the charging plan (e.g., for a station) isdetermined at least partially based on a type (e.g., the types ofbatteries as discussed above) of the energy storage devices of thedevice-exchange station. Based on the charging plan, the system candetermine one or more suitable charging rules for each of the energystorage devices. The system can then generate charging commands (e.g.,particular instructions for the station to implement) and transmit thesame to the device-exchange station.

In some embodiments, the charging command can be generated at leastpartially based on a charger type of a charger positioned in thedevice-exchange station (e.g., battery exchange stations 107, 207,station system 300 or client station 40). The charger is configured tocharge one or more of the energy storage devices. For example, thecharger type can include a one-versus-one type (e.g., one battery, onecharger), a two-versus-one type (e.g., two batteries share one charger),or a four-versus-one type (e.g., four batteries share one charger). Insuch embodiments, the system considers the availability of charger whenit determines the charging plan. For example, referring to FIG. 2, theslots 217 d, 217 h can share one charger, and accordingly there is onebattery in the slots 217 d, 217 h can be charged at one time.

In some embodiments, the device-exchange station (e.g., battery exchangestations 107, 207, station system 300 or client station 40) can be afirst device-exchange station, and the method can include determiningthe charging plan for the first device-exchange station at leastpartially based on a status of a second device-exchange station adjacentto or near by the first device-exchange station. For example, when theservice provided by the second device-exchange station is interrupted(e.g., due to a maintenance event or a power outage), the system canadjust its charging plan for the first station to address the predicteddemands for the second station.

In some embodiments, the method can include assigning a priority valueto each of the exchangeable energy storage devices (e.g., based on theirSoCs) positioned in the device-exchange station. The method can alsoinclude determining the charging plan for the device-exchange station atleast partially based on the priority value. Please refer to theforegoing embodiments associated with batteries B1-B6. Based on thepriority values, the system can determine which batteries to be chargedfirst and exchanged first.

Although the present technology has been described with reference tospecific exemplary embodiments, it will be recognized that the presenttechnology is not limited to the embodiments described but can bepracticed with modification and alteration within the spirit and scopeof the appended claims. Accordingly, the specification and drawings areto be regarded in an illustrative sense rather than a restrictive sense.

The invention claimed is:
 1. A method for charging exchangeable energystorage devices positioned in a device-exchange station, the methodcomprising: receiving demand information for the device-exchangestation; determining a charging plan for the device-exchange station atleast partially based on a state-of-charge (SoC) of each of theexchangeable energy storage devices positioned in the device-exchangestation, the demand information, and an available power of thedevice-exchange station, the charging plan including at least onecharging rule for each of the exchangeable energy storage devicespositioned in the device-exchange station; generating a charging commandfor each of the exchangeable energy storage devices based on thecharging rule for each of the exchangeable energy storage devices; andtransmitting the charging commands to the device-exchange station. 2.The method of claim 1, further comprising: periodically updating thecharging plan for the device-exchange station; and updating the chargingplan in response to the triggering event on the device-exchange station.3. The method of claim 1, further comprising customizing the at leastone charging rule for each of the exchangeable energy storage devicesbased on a predetermined objective.
 4. The method of claim 3, furthercomprising adjusting the charging plan based on an economic condition.5. The method of claim 1, wherein the charging plan is determined atleast partially based on a type of the energy storage devices of thedevice-exchange station.
 6. The method of claim 5, wherein the type ofthe device-exchange station includes a public type, a semi-private type,or a private type.
 7. The method of claim 1, wherein the chargingcommand is generated at least partially based on a charger type of acharger positioned in the device-exchange station.
 8. The method ofclaim 7, wherein the charger type includes a one-versus-one type, atwo-versus-one type, or a four-versus-one type.
 9. The method of claim1, wherein the device-exchange station is a first device-exchangestation, and wherein the method comprises: determining the charging planfor the first device-exchange station at least partially based on astatus of a second device-exchange station adjacent to the firstdevice-exchange station.
 10. The method of claim 9, wherein the statusof the second device-exchange station includes a normal status or aservice-interrupted status, and wherein the service-interrupted statusresults from a maintenance event or a power outage.
 11. The method ofclaim 1, further comprising: assigning a priority value to each of theexchangeable energy storage devices positioned in the device-exchangestation; and determining the charging plan for the device-exchangestation at least partially based on the priority value and the demandinformation.
 12. The method of claim 11, wherein the priority value isdetermined based on the SoC of each of the exchangeable energy storagedevices positioned in the device-exchange station.
 13. The method ofclaim 1, further comprising: categorizing the exchangeable energystorage devices positioned in the device-exchange station into a firstgroup, a second group, and a third group, wherein the first groupincludes the exchangeable energy storage devices that have more than anSoC threshold and that are not locked, and wherein the second groupincludes the exchangeable energy storage devices that have less than theSoC threshold and that are not locked, and wherein the third groupincludes the exchangeable energy storage devices that are locked; anddetermining the charging plan for the device-exchange station at leastpartially based on numbers exchangeable energy storage devices in thefirst group, the second group, and the third group.
 14. The method ofclaim 1, wherein the demand information includes a first demandprediction for a first hour and a second demand prediction for a secondhour following the first hour.
 15. The method of claim 14, furthercomprising: assigning a priority value to each of the exchangeableenergy storage devices positioned in the device-exchange station; anddetermining the charging plan for the device-exchange station at leastpartially based on the priority value and the first demand predictionand the second demand prediction.
 16. The method of claim 1, wherein theat least one charging rule is determined based on one or morecharacteristics of the exchangeable energy storage devices, and whereinthe one or more characteristics incudes a current temperature, batterymanufacturing information, battery characteristic information, batterycharging information or battery usage information.
 17. The method ofclaim 1, wherein the at least one charging rule includes a firstcharging rule or a second charging rule, and wherein the method furthercomprises determining whether to use the first charging rule or thesecond charging rule based on the demand information, where in the firstcharging rule corresponds to a first charging rate greater than a secondcharging rate corresponding to the second charging rule.
 18. A servercomprising: a processor configured to— receive demand information for adevice-exchange station; determine a charging plan for thedevice-exchange station at least partially based on a state-of-charge(SoC) of each of exchangeable energy storage devices positioned in thedevice-exchange station, the demand information, and an available powerof the device-exchange station, the charging plan including at least onecharging rule for each of the exchangeable energy storage devicespositioned in the device-exchange station; generate a charging commandfor each of the exchangeable energy storage devices based on thecharging rule for each of the exchangeable energy storage devices; andtransmit, via a communication component, the charging commands to thedevice-exchange station.
 19. The system of claim 18, wherein theprocessor is configured to update the charging plan in response to atriggering event, and wherein the triggering event includes an exchangeof the exchangeable energy storage devices positioned in thedevice-exchange station, a change to the available power, a change tothe demand information, or a reservation for the exchangeable energystorage devices positioned in the device-exchange station.
 20. A methodfor managing a device-exchange station, the method comprising: receivinga plurality of predicted exchange demands for the device-exchangestation; determining a charging plan for the device-exchange station atleast partially based on a state-of-charge (SoC) and a temperature ofeach of the exchangeable energy storage devices positioned in thedevice-exchange station, the plurality of predicted exchange demands,and an available power of the device-exchange station, the charging planincluding at least one charging rule for each of the exchangeable energystorage devices positioned in the device-exchange station; generating acharging command for each of the exchangeable energy storage devicesbased on the charging rule for each of the exchangeable energy storagedevices; and transmitting the charging commands to the device-exchangestation.